Literature DB >> 30810359

Bioinformatics Analysis of Key Genes and Pathways in Colorectal Cancer.

Yuewen Qi1, Haowen Qi2, Zeyuan Liu3, Peiyuan He1, Bingqing Li1.   

Abstract

Colorectal cancer (CRC) is the third most prevalent cancer in the world. Although great progress has been made, the specific molecular mechanism remains unclear. This study aimed to explore the differentially expressed genes (DEGs) and underlying mechanisms of CRC using bioinformatics analysis. In this study, we identified a total of 1353 DEGs in the database of GSE113513, including 715 up- and 638 downregulated genes. Gene ontology analysis results showed that upregulated DEGs were significantly enriched in cell division, cell proliferation, and DNA replication. The downregulated DEGs were enriched in immune response, relation of cell growth and inflammatory response. The Kyoto Encyclopedia of Genes and Genomes pathway analysis showed that upregulated DEGs were enriched in cell cycle and p53 signaling pathway, whereas the downregulated DEGs were enriched in drug metabolism, metabolism of xenobiotics by cytochrome P450, and nitrogen metabolism. A total of 124 up-key genes and 35 down-key genes were identified from the protein-protein interaction networks. Furthermore, we identified five up-modules (up-A, up-B, up-C, up-D, and up-E) and three down-modules (d-A, d-B, and d-C) by module analysis. The module up-A was enriched in sister chromatid cohesion, cell division, and mitotic nuclear division. Pathways associated with cell cycle, progesterone-mediated oocyte maturation, oocyte meiosis, and p53 signaling pathway. Whereas the d-A was mainly enriched in G-protein coupled receptor signaling pathway, cell chemotaxis, and chemokine-mediated signaling pathway. The pathways enriched in chemokine signaling pathway, cytokine-cytokine receptor interaction, and alcoholism. These key genes and pathways might be used as molecular targets and diagnostic biomarkers for the treatment of CRC.

Entities:  

Keywords:  colorectal cancer; key genes; molecular mechanisms

Mesh:

Substances:

Year:  2019        PMID: 30810359     DOI: 10.1089/cmb.2018.0237

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  7 in total

1.  Identification of key candidate genes and pathways associated with colorectal aberrant crypt foci-to-adenoma-to-carcinoma progression.

Authors:  Setareh Fayazfar; Afsaneh Arefi Oskouie; Akram Safaei; Hakimeh Zali; Ehsan Nazemalhosseini Mojarad
Journal:  Gastroenterol Hepatol Bed Bench       Date:  2021

2.  IL-8, MSPa, MIF, FGF-9, ANG-2 and AgRP collection were identified for the diagnosis of colorectal cancer based on the support vector machine model.

Authors:  Mingfu Cui; Yanan Zhao; Zuocong Zhang; Yang Zhao; Songyun Han; Ruijie Wang; Dayong Ding; Xuedong Fang
Journal:  Cell Cycle       Date:  2021-03-28       Impact factor: 4.534

3.  Colon Cancer Progression Is Reflected to Monotonic Differentiation in Gene Expression and Pathway Deregulation Facilitating Stage-specific Drug Repurposing.

Authors:  Marilena M Bourdakou; George M Spyrou; George Kolios
Journal:  Cancer Genomics Proteomics       Date:  2021 Nov-Dec       Impact factor: 4.069

4.  Prognostic relevance of SMC family gene expression in human sarcoma.

Authors:  Jian Zhou; Gen Wu; Zhongyi Tong; Jingjing Sun; Jing Su; Ziqin Cao; Yingquan Luo; Wanchun Wang
Journal:  Aging (Albany NY)       Date:  2020-12-30       Impact factor: 5.682

5.  Modular Reorganization of Signaling Networks during the Development of Colon Adenoma and Carcinoma.

Authors:  Klára Schulc; Zsolt T Nagy; Sebestyén Kamp; János Molnár; Daniel V Veres; Peter Csermely; Borbála M Kovács
Journal:  J Phys Chem B       Date:  2021-02-09       Impact factor: 2.991

6.  CX3CR1 Acts as a Protective Biomarker in the Tumor Microenvironment of Colorectal Cancer.

Authors:  Yuanyi Yue; Qiang Zhang; Zhengrong Sun
Journal:  Front Immunol       Date:  2022-01-24       Impact factor: 7.561

7.  Identification of Hub Genes Using Co-Expression Network Analysis in Breast Cancer as a Tool to Predict Different Stages.

Authors:  Yun Fu; Qu-Zhi Zhou; Xiao-Lei Zhang; Zhen-Zhen Wang; Peng Wang
Journal:  Med Sci Monit       Date:  2019-11-23
  7 in total

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